1. Field of the Invention
This invention relates to computing systems and, more particularly, to combining query results for multiple, similar queries according to user feedback on the query results.
2. Description of the Related Art
The Internet can be viewed as a large collection of documents, for example, text files, web-pages, newsgroup postings or pictures. To locate documents on the Internet, users typically use an Internet search engine. The user would enter one or more key words and perhaps indicate Boolean operators for the search, and transmit the search request to a server including a search engine. Search engines include a spider program or crawler that periodically visits web pages and searches the Internet to locate new web pages and revise previously located sites to look for changes. The spider then places information from the pages it locates into a database index that relates URLs to search terms.
Internet search engines provide a means of searching through the vast amount of documents to produce a results list of the documents found which match the terms in a search query. Typically the results list is presented as a list of document summaries that includes hyperlinks (“links”) that connect each entry to the appropriate Internet document. The results list is generally ranked by relevance (in relation to the query), with each entry included in the list presented either higher or lower on the list according to the relevance ranking as determined by the search engine being used. The way in which these relevance rankings are determined is constantly evolving as the Internet continues to evolve.
On the Internet, search queries are processed by search tools known as “search engines” that typically present a sequential list of matching data items ranked by relevance, from most relevant to least relevant. As a result, the matching data items that best satisfy the search criteria are presented at the top of the list, with the other matching data items presented further down the list in order of decreasing relevance. For example, web pages or web sites with web pages that contain the greatest number of the search terms receive the highest relevance ranking and are presented at the top of the list.
Search engines apply different algorithms to “filter” the available documents and assign relevance rankings to the documents reviewed. The relevance rankings are generally stored in a search index that corresponds to documents for a specific search term (or related search terms). A search engine may locate numerous search results in response to a user search query, many of which may not be relevant. One problem search engine developers must address is the order in which to present the search results. Most search engines use the location and frequency of keywords on a web page as the basis of ranking search results. Other search engines may boost a page's display order if search keywords are included in the meta description and keywords tag of the page. A search engine can also provide a relevancy boost based on the number of pages and/or number of important web pages that include hypertext links to the search result page.
Today's search engines index in excess of 10 billion documents and are the method of choice for finding online content. Although the relevance of search results has been improving with the introduction of ranking based on link counts and similar mechanisms, search engines continue to deliver search results that frustrate users. Consequently, users have come to expect that identifying the correct query to achieve the right results is a process of trial and error. Search engines receive high traffic volumes each day, often by users looking for the same or similar things.